U.S. patent application number 15/783046 was filed with the patent office on 2019-04-18 for determining a safe driving speed for a vehicle.
The applicant listed for this patent is INTERNATIONAL BUSINESS MACHINES CORPORATION. Invention is credited to GREGG M. ARQUERO, STEVEN N. BURCHFIELD.
Application Number | 20190111923 15/783046 |
Document ID | / |
Family ID | 66097365 |
Filed Date | 2019-04-18 |
![](/patent/app/20190111923/US20190111923A1-20190418-D00000.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00001.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00002.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00003.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00004.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00005.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00006.png)
![](/patent/app/20190111923/US20190111923A1-20190418-D00007.png)
United States Patent
Application |
20190111923 |
Kind Code |
A1 |
ARQUERO; GREGG M. ; et
al. |
April 18, 2019 |
DETERMINING A SAFE DRIVING SPEED FOR A VEHICLE
Abstract
Embodiments include methods, systems and computer program
products for determining a safe driving speed for a vehicle.
Aspects include obtaining a location and a direction of travel of
the vehicle, obtaining one or more operating conditions of the
vehicle, and obtaining historical accident data that corresponds to
the location of the vehicle under operating conditions that are
similar to the one or more conditions of the vehicle. Aspects also
include analyzing, by a processor, the historical accident data to
identify the safe driving speed for the vehicle, wherein the safe
driving speed is determined to be a maximum speed that is
associated with maximum acceptable risk of an accident and causing
an indication of the safe driving speed to be displayed to an
operator of the vehicle.
Inventors: |
ARQUERO; GREGG M.;
(POUGHKEEPSIE, NY) ; BURCHFIELD; STEVEN N.;
(WOODSTOCK, NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INTERNATIONAL BUSINESS MACHINES CORPORATION |
ARMONK |
NY |
US |
|
|
Family ID: |
66097365 |
Appl. No.: |
15/783046 |
Filed: |
October 13, 2017 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 40/08 20130101;
G08G 1/0112 20130101; B60W 2556/50 20200201; B60W 2050/143
20130101; G08G 1/012 20130101; G08G 1/0141 20130101; G08G 1/096741
20130101; B60W 2720/10 20130101; G08G 1/096725 20130101; B60W
2555/20 20200201; B60W 2720/12 20130101; B60W 2554/00 20200201;
B60W 30/146 20130101; G08G 1/096708 20130101; G08G 1/052 20130101;
B60W 30/162 20130101; B60W 2556/45 20200201; G06Q 50/265 20130101;
B60W 50/14 20130101; G08G 1/096775 20130101; G08G 1/096716
20130101; G08G 1/0129 20130101 |
International
Class: |
B60W 30/14 20060101
B60W030/14; G08G 1/052 20060101 G08G001/052; G08G 1/01 20060101
G08G001/01 |
Claims
1. A computer implemented method determining a safe driving speed
for a vehicle, the computer implemented method comprises: obtaining
a location and a direction of travel of the vehicle; obtaining one
or more operating conditions of the vehicle; obtaining historical
accident data that corresponds to the location of the vehicle under
operating conditions that are similar to the one or more conditions
of the vehicle; analyzing, by a processor, the historical accident
data to identify the safe driving speed for the vehicle, wherein
the safe driving speed is determined to be a maximum speed that is
associated with maximum acceptable risk of an accident; and causing
an indication of the safe driving speed to be displayed to an
operator of the vehicle.
2. The computer implemented method of claim 1, further comprising
generating an alert based on a determination that a current speed
of the vehicle is greater than the safe driving speed.
3. The computer implemented method of claim 1, further comprising
limiting a current speed of the vehicle to the safe driving
speed.
4. The computer implemented method of claim 1, further comprising
adjusting a speed of a cruise control of the vehicle to be equal to
the safe driving speed.
5. The computer implemented method of claim 1, wherein the one or
more operating conditions of the vehicle comprise a weather
condition of the location and a time of day at the location.
6. The computer implemented method of claim 1, wherein analyzing
the historical accident data to identify the safe driving speed for
the vehicle includes creating a graph of the historical accident
data and identifying an inflection point in the graph as the safe
driving speed.
7. The computer implemented method of claim 1, wherein the
historical accident data is obtained from a vehicle accident
database that includes accident data from one or more of an
insurance database and a police record database.
8. A computer program product for determining a safe driving speed
for a vehicle, the computer program product comprising: a storage
medium readable by a processing circuit and storing instructions
for execution by the processing circuit for performing a method
comprising: obtaining a location and a direction of travel of the
vehicle; obtaining one or more operating conditions of the vehicle;
obtaining historical accident data that corresponds to the location
of the vehicle under operating conditions that are similar to the
one or more conditions of the vehicle; analyzing, by a processor,
the historical accident data to identify the safe driving speed for
the vehicle, wherein the safe driving speed is determined to be a
maximum speed that is associated with maximum acceptable risk of an
accident; and causing an indication of the safe driving speed to be
displayed to an operator of the vehicle.
9. The computer program product of claim 8, further comprising
generating an alert based on a determination that a current speed
of the vehicle is greater than the safe driving speed.
10. The computer program product of claim 8, further comprising
limiting a current speed of the vehicle to the safe driving
speed.
11. The computer program product of claim 8, further comprising
adjusting a speed of a cruise control of the vehicle to be equal to
the safe driving speed.
12. The computer program product of claim 8, wherein the one or
more operating conditions of the vehicle comprise a weather
condition of the location and a time of day at the location.
13. The computer program product of claim 8, wherein analyzing the
historical accident data to identify the safe driving speed for the
vehicle includes creating a graph of the historical accident data
and identifying an inflection point in the graph as the safe
driving speed.
14. The computer program product of claim 8, wherein the historical
accident data is obtained from a vehicle accident database that
includes accident data from one or more of an insurance database
and a police record database.
15. A system configured to determine a safe driving speed for a
vehicle, the system comprising a processor in communication with
one or more types of memory, the processor configured to: obtain a
location and a direction of travel of the vehicle; obtain one or
more operating conditions of the vehicle; obtain historical
accident data that corresponds to the location of the vehicle under
operating conditions that are similar to the one or more conditions
of the vehicle; analyze, the historical accident data to identify
the safe driving speed for the vehicle, wherein the safe driving
speed is determined to be a maximum speed that is associated with
maximum acceptable risk of an accident; and display an indication
of the safe driving speed to an operator of the vehicle.
16. The system of claim 15, wherein the processor is further
configured to generate an alert based on a determination that a
current speed of the vehicle is greater than the safe driving
speed.
17. The system of claim 15, wherein the processor is further
configured to limit a current speed of the vehicle to the safe
driving speed.
18. The system of claim 15, wherein the processor is further
configured to adjust a speed of a cruise control of the vehicle to
be equal to the safe driving speed.
19. The system of claim 15, wherein the one or more operating
conditions of the vehicle comprise a weather condition of the
location and a time of day at the location.
20. The system of claim 15, wherein analyzing the historical
accident data to identify the safe driving speed for the vehicle
includes creating a graph of the historical accident data and
identifying a maximum speed at which a percentage of vehicles
traveling below a threshold value.
Description
BACKGROUND
[0001] The present disclosure relates to operating a vehicle and
more specifically, to methods, systems and computer program
products for determining a safe speed for driving a vehicle.
[0002] In general, speed limits are provided for large sections of
roads, these speed limits reflect a maximum allowable speed for
traveling on the road. These speed limits do not account for
variances in the weather conditions, the time of day, or for
increased accident risk of specific portions of the road.
Currently, there is no consistent way for an operator of a vehicle
to determine at what speed, for all sections of a road, an accident
is likely to occur. Rather, operators often have to rely on
instinct and past experience in the immediate area to have an idea
at which speed it is safe to travel.
SUMMARY
[0003] In accordance with an embodiment, a method for determining a
safe driving speed for a vehicle is provided. The method includes
obtaining a location and a direction of travel of the vehicle,
obtaining one or more operating conditions of the vehicle, and
obtaining historical accident data that corresponds to the location
of the vehicle under operating conditions that are similar to the
one or more conditions of the vehicle. The method also includes
analyzing the historical accident data to identify the safe driving
speed for the vehicle, wherein the safe driving speed is determined
to be a maximum speed that is associated with maximum acceptable
risk of an accident. The method further includes causing an
indication of the safe driving speed to be displayed to an operator
of the vehicle.
[0004] In accordance with another embodiment, a system for
determining a safe driving speed for a vehicle is provided. The
mobile device includes a processor in communication with one or
more types of memory. The processor is configured to obtain a
location and a direction of travel of the vehicle, obtain one or
more operating conditions of the vehicle, and obtain historical
accident data that corresponds to the location of the vehicle under
operating conditions that are similar to the one or more conditions
of the vehicle. The processor is further configured to analyze the
historical accident data to identify the safe driving speed for the
vehicle, wherein the safe driving speed is determined to be a
maximum speed that is associated with maximum acceptable risk of an
accident. The processor is also configured to cause an indication
of the safe driving speed to be displayed to an operator of the
vehicle.
[0005] In accordance with a further embodiment, a computer program
product for determining a safe driving speed for a vehicle includes
a non-transitory storage medium readable by a processing circuit
and storing instructions for execution by the processing circuit
for performing a method. The method includes obtaining a location
and a direction of travel of the vehicle, obtaining one or more
operating conditions of the vehicle, and obtaining historical
accident data that corresponds to the location of the vehicle under
operating conditions that are similar to the one or more conditions
of the vehicle. The method also includes analyzing the historical
accident data to identify the safe driving speed for the vehicle,
wherein the safe driving speed is determined to be a maximum speed
that is associated with maximum acceptable risk of an accident. The
method further includes causing an indication of the safe driving
speed to be displayed to an operator of the vehicle.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] The subject matter which is regarded as the invention is
particularly pointed out and distinctly claimed in the claims at
the conclusion of the specification. The foregoing and other
features, and advantages of the invention are apparent from the
following detailed description taken in conjunction with the
accompanying drawings in which:
[0007] FIG. 1 depicts a cloud computing environment according to
one or more embodiments of the present invention;
[0008] FIG. 2 depicts abstraction model layers according to one or
more embodiments of the present invention;
[0009] FIG. 3 is a block diagram of an exemplary computer system
capable of implementing one or more embodiments of the present
invention;
[0010] FIG. 4 is a block diagram of a system for determining a safe
driving speed for a vehicle in accordance with an exemplary
embodiment;
[0011] FIG. 5 is a flow diagram of method for determining a safe
driving speed for a vehicle in accordance with an exemplary
embodiment;
[0012] FIG. 6 is a flow diagram of another method for determining a
safe driving speed for a vehicle in accordance with an exemplary
embodiment;
[0013] FIG. 7 is a graph illustrating a normalized number of
accidents and the speed at which the accident occurred for a
segment of a road in accordance with an exemplary embodiment;
and
[0014] FIG. 8 is a graph illustrating a normalized number of
accidents and the speed at which the accident occurred for a
segment of a road in accordance with an exemplary embodiment.
DETAILED DESCRIPTION
[0015] Various embodiments of the invention are described herein
with reference to the related drawings. Alternative embodiments of
the invention can be devised without departing from the scope of
this invention. Various connections and positional relationships
(e.g., over, below, adjacent, etc.) are set forth between elements
in the following description and in the drawings. These connections
and/or positional relationships, unless specified otherwise, can be
direct or indirect, and the present invention is not intended to be
limiting in this respect. Accordingly, a coupling of entities can
refer to either a direct or an indirect coupling, and a positional
relationship between entities can be a direct or indirect
positional relationship. Moreover, the various tasks and process
steps described herein can be incorporated into a more
comprehensive procedure or process having additional steps or
functionality not described in detail herein.
[0016] The following definitions and abbreviations are to be used
for the interpretation of the claims and the specification. As used
herein, the terms "comprises," "comprising," "includes,"
"including," "has," "having," "contains" or "containing," or any
other variation thereof, are intended to cover a non-exclusive
inclusion. For example, a composition, a mixture, a process, a
method, an article, or an apparatus that comprises a list of
elements is not necessarily limited to only those elements but can
include other elements not expressly listed or inherent to such
composition, mixture, process, method, article, or apparatus.
[0017] Additionally, the term "exemplary" is used herein to mean
"serving as an example, instance or illustration." Any embodiment
or design described herein as "exemplary" is not necessarily to be
construed as preferred or advantageous over other embodiments or
designs. The terms "at least one" and "one or more" may be
understood to include any integer number greater than or equal to
one, i.e. one, two, three, four, etc. The terms "a plurality" may
be understood to include any integer number greater than or equal
to two, i.e. two, three, four, five, etc. The term "connection" may
include both an indirect "connection" and a direct
"connection."
[0018] The terms "about," "substantially," "approximately," and
variations thereof, are intended to include the degree of error
associated with measurement of the particular quantity based upon
the equipment available at the time of filing the application. For
example, "about" can include a range of .+-.8% or 5%, or 2% of a
given value.
[0019] For the sake of brevity, conventional techniques related to
making and using aspects of the invention may or may not be
described in detail herein. In particular, various aspects of
computing systems and specific computer programs to implement the
various technical features described herein are well known.
Accordingly, in the interest of brevity, many conventional
implementation details are only mentioned briefly herein or are
omitted entirely without providing the well-known system and/or
process details.
[0020] It is to be understood that although this disclosure
includes a detailed description on cloud computing, implementation
of the teachings recited herein are not limited to a cloud
computing environment. Rather, embodiments of the present invention
are capable of being implemented in conjunction with any other type
of computing environment now known or later developed.
[0021] Cloud computing is a model of service delivery for enabling
convenient, on-demand network access to a shared pool of
configurable computing resources (e.g., networks, network
bandwidth, servers, processing, memory, storage, applications,
virtual machines, and services) that can be rapidly provisioned and
released with minimal management effort or interaction with a
provider of the service. This cloud model may include at least five
characteristics, at least three service models, and at least four
deployment models.
[0022] Characteristics are as follows:
[0023] On-demand self-service: a cloud consumer can unilaterally
provision computing capabilities, such as server time and network
storage, as needed automatically without requiring human
interaction with the service's provider.
[0024] Broad network access: capabilities are available over a
network and accessed through standard mechanisms that promote use
by heterogeneous thin or thick client platforms (e.g., mobile
phones, laptops, and PDAs).
[0025] Resource pooling: the provider's computing resources are
pooled to serve multiple consumers using a multi-tenant model, with
different physical and virtual resources dynamically assigned and
reassigned according to demand. There is a sense of location
independence in that the consumer generally has no control or
knowledge over the exact location of the provided resources but may
be able to specify location at a higher level of abstraction (e.g.,
country, state, or datacenter).
[0026] Rapid elasticity: capabilities can be rapidly and
elastically provisioned, in some cases automatically, to quickly
scale out and rapidly released to quickly scale in. To the
consumer, the capabilities available for provisioning often appear
to be unlimited and can be purchased in any quantity at any
time.
[0027] Measured service: cloud systems automatically control and
optimize resource use by leveraging a metering capability at some
level of abstraction appropriate to the type of service (e.g.,
storage, processing, bandwidth, and active user accounts). Resource
usage can be monitored, controlled, and reported, providing
transparency for both the provider and consumer of the utilized
service.
[0028] Service Models are as follows:
[0029] Software as a Service (SaaS): the capability provided to the
consumer is to use the provider's applications running on a cloud
infrastructure. The applications are accessible from various client
devices through a thin client interface such as a web browser
(e.g., web-based e-mail). The consumer does not manage or control
the underlying cloud infrastructure including network, servers,
operating systems, storage, or even individual application
capabilities, with the possible exception of limited user-specific
application configuration settings.
[0030] Platform as a Service (PaaS): the capability provided to the
consumer is to deploy onto the cloud infrastructure
consumer-created or acquired applications created using programming
languages and tools supported by the provider. The consumer does
not manage or control the underlying cloud infrastructure including
networks, servers, operating systems, or storage, but has control
over the deployed applications and possibly application hosting
environment configurations.
[0031] Infrastructure as a Service (IaaS): the capability provided
to the consumer is to provision processing, storage, networks, and
other fundamental computing resources where the consumer is able to
deploy and run arbitrary software, which can include operating
systems and applications. The consumer does not manage or control
the underlying cloud infrastructure but has control over operating
systems, storage, deployed applications, and possibly limited
control of select networking components (e.g., host firewalls).
[0032] Deployment Models are as follows:
[0033] Private cloud: the cloud infrastructure is operated solely
for an organization. It may be managed by the organization or a
third party and may exist on-premises or off-premises.
[0034] Community cloud: the cloud infrastructure is shared by
several organizations and supports a specific community that has
shared concerns (e.g., mission, security requirements, policy, and
compliance considerations). It may be managed by the organizations
or a third party and may exist on-premises or off-premises.
[0035] Public cloud: the cloud infrastructure is made available to
the general public or a large industry group and is owned by an
organization selling cloud services.
[0036] Hybrid cloud: the cloud infrastructure is a composition of
two or more clouds (private, community, or public) that remain
unique entities but are bound together by standardized or
proprietary technology that enables data and application
portability (e.g., cloud bursting for load-balancing between
clouds).
[0037] A cloud computing environment is service oriented with a
focus on statelessness, low coupling, modularity, and semantic
interoperability. At the heart of cloud computing is an
infrastructure that includes a network of interconnected nodes.
[0038] Referring now to FIG. 1, illustrative cloud computing
environment 50 is depicted. As shown, cloud computing environment
50 includes one or more cloud computing nodes 10 with which local
computing devices used by cloud consumers, such as, for example,
personal digital assistant (PDA) or cellular telephone 54A, desktop
computer 54B, laptop computer 54C, and/or automobile computer
system 54N may communicate. Nodes 10 may communicate with one
another. They may be grouped (not shown) physically or virtually,
in one or more networks, such as Private, Community, Public, or
Hybrid clouds as described hereinabove, or a combination thereof.
This allows cloud computing environment 50 to offer infrastructure,
platforms and/or software as services for which a cloud consumer
does not need to maintain resources on a local computing device. It
is understood that the types of computing devices 54A-N shown in
FIG. 1 are intended to be illustrative only and that computing
nodes 10 and cloud computing environment 50 can communicate with
any type of computerized device over any type of network and/or
network addressable connection (e.g., using a web browser).
[0039] Referring now to FIG. 2, a set of functional abstraction
layers provided by cloud computing environment 50 (FIG. 1) is
shown. It should be understood in advance that the components,
layers, and functions shown in FIG. 2 are intended to be
illustrative only and embodiments of the invention are not limited
thereto. As depicted, the following layers and corresponding
functions are provided:
[0040] Hardware and software layer 60 includes hardware and
software components. Examples of hardware components include:
mainframes 61; RISC (Reduced Instruction Set Computer) architecture
based servers 62; servers 63; blade servers 64; storage devices 65;
and networks and networking components 66. In some embodiments,
software components include network application server software 67
and database software 68.
[0041] Virtualization layer 70 provides an abstraction layer from
which the following examples of virtual entities may be provided:
virtual servers 71; virtual storage 72; virtual networks 73,
including virtual private networks; virtual applications and
operating systems 74; and virtual clients 75.
[0042] In one example, management layer 80 may provide the
functions described below. Resource provisioning 81 provides
dynamic procurement of computing resources and other resources that
are utilized to perform tasks within the cloud computing
environment. Metering and Pricing 82 provide cost tracking as
resources are utilized within the cloud computing environment, and
billing or invoicing for consumption of these resources. In one
example, these resources may include application software licenses.
Security provides identity verification for cloud consumers and
tasks, as well as protection for data and other resources. User
portal 83 provides access to the cloud computing environment for
consumers and system administrators. Service level management 84
provides cloud computing resource allocation and management such
that required service levels are met. Service Level Agreement (SLA)
planning and fulfillment 85 provides pre-arrangement for, and
procurement of, cloud computing resources for which a future
requirement is anticipated in accordance with an SLA.
[0043] Workloads layer 90 provides examples of functionality for
which the cloud computing environment may be utilized. Examples of
workloads and functions which may be provided from this layer
include: mapping and navigation 91; software development and
lifecycle management 92; virtual classroom education delivery 93;
data analytics processing 94; transaction processing 95; and
analysis of accident data 96.
[0044] Referring to FIG. 3, there is shown an embodiment of a
processing system 100 for implementing the teachings herein. In
this embodiment, the system 100 has one or more central processing
units (processors) 101a, 101b, 101c, etc. (collectively or
generically referred to as processor(s) 101). In one embodiment,
each processor 101 may include a reduced instruction set computer
(RISC) microprocessor. Processors 101 are coupled to system memory
114 and various other components via a system bus 113. Read-only
memory (ROM) 102 is coupled to the system bus 113 and may include a
basic input/output system (BIOS), which controls certain basic
functions of system 100.
[0045] FIG. 3 further depicts an input/output (I/O) adapter 107, a
network adapter 106, and a GPS device 140 coupled to the system bus
113. I/O adapter 107 may be a small computer system interface
(SCSI) adapter that communicates with flash storage, a hard disk
103 and/or tape storage drive 105 or any other similar component.
I/O adapter 107, flash storage, hard disk 103, and tape storage
device 105 are collectively referred to herein as mass storage 104.
Operating system 120 for execution on the processing system 100 may
be stored in mass storage 104. A network adapter 106 interconnects
bus 113 with an outside network 116 enabling data processing system
100 to communicate with other such systems. A screen (e.g., a
display monitor) 115 is connected to system bus 113 by display
adaptor 112, which may include a graphics adapter to improve the
performance of graphics intensive applications and a video
controller. In one embodiment, adapters 107, 106, and 112 may be
connected to one or more I/O busses that are connected to system
bus 113 via an intermediate bus bridge (not shown). Suitable I/O
buses for connecting peripheral devices such as hard disk
controllers, network adapters, and graphics adapters typically
include common protocols, such as the Peripheral Component
Interconnect (PCI). Additional input/output devices are shown as
connected to system bus 113 via user interface adapter 108 and
display adapter 112. A keyboard 109, mouse 110, and speaker 111 all
interconnected to bus 113 via user interface adapter 108, which may
include, for example, a Super I/O chip integrating multiple device
adapters into a single integrated circuit.
[0046] In exemplary embodiments, the processing system 100 includes
a graphics processing unit 130. Graphics processing unit 130 is a
specialized electronic circuit designed to manipulate and alter
memory to accelerate the creation of images in a frame buffer
intended for output to a display.
[0047] Thus, as configured in FIG. 3, the system 100 includes
processing capability in the form of processors 101, storage
capability including system memory 114 and mass storage 104, input
means such as keyboard 109 and mouse 110, and output capability
including speaker 111 and display 115. In one embodiment, a portion
of system memory 114 and mass storage 104 collectively store an
operating system to coordinate the functions of the various
components shown in FIG. 3.
[0048] Turning now to an overview of technologies that are more
specifically relevant to aspects of the invention, which are
related to determining a safe driving speed for a vehicle. In
exemplary embodiments, historical accident data is obtained that
includes information regarding accidents that occurred on a portion
of a road that the vehicle is on. From this accident data, and
based on the current driving conditions, a safe speed at which
drivers can drive such that an accident is unlikely to occur is
calculated. In exemplary embodiments, the historical accident data
includes the location of the accidents that occurred, the speed at
which the accident occurred, the time of day that the accident
occurred, the day of the week that the accident occurred, the
weather at the time that the accident occurred, the traffic density
that the accident occurred, and the like.
[0049] Referring now to FIG. 4, a system 200 for determining a safe
driving speed for a vehicle is shown. As illustrated the system 200
includes a mobile device 202 that includes a GPS receiver 204, a
communications device 206 and a user interface 208. In exemplary
embodiments, the mobile device 202 can be a vehicle or it may be a
smartphone disposed within a vehicle. The mobile device 202 is
configured to communicate with one or more of a processing system
210, an incident database 212, and a weather database 214 via a
communications network 220. The processing system 210, may be a
processing system such as the one shown in FIG. 3, and the
processing system 210 is configured to communicate with one or more
of the incident database 212 and the weather database 214 via a
communications network 220. The communications network 220 can
include both private and public communications networks such as
cellular telephone networks, and the Internet.
[0050] In exemplary embodiments, the safe driving speed calculation
can be performed by the mobile device 202 or by the processing
system 210 based on data obtained from the mobile device 202, the
weather database 214 and the incident database(s) 212. In exemplary
embodiments, the incident database(s) 212 can include data obtained
from police records and/or insurance records. The incident
database(s) 212 can include a location of the accident, a speed at
which the driver was traveling, a date and time of day of the
accident and the weather conditions at the time of the accident. In
exemplary embodiments, the incident database(s) 212 can include
data from the past five years from a current date.
[0051] Referring now to FIG. 5, a flow diagram of a method 300
determining a safe driving speed for a vehicle in accordance with
an exemplary embodiment. As shown at block 302, the method 300
includes obtaining a location and a direction of travel of the
vehicle. Next, as shown at block 304, the method 300 includes
obtaining one or more operating conditions of the vehicle. In
exemplary embodiments, the one or more operating conditions of the
vehicle include a weather condition of the location and a time of
day at the location of the vehicle. The method 300 also includes
obtaining historical accident data that corresponds to the location
of the vehicle under operating conditions that are similar to the
one or more conditions of the vehicle, as shown at block 306. In
exemplary embodiments, the historical accident data is obtained
from a vehicle accident database that includes accident data from
one or more of an insurance database and a police record database.
Next, as shown at block 308, the method 300 includes analyzing the
historical accident data to identify the safe driving speed for the
vehicle. In one embodiment, analyzing the historical accident data
to identify the safe driving speed for the vehicle includes
creating a graph of the accident data and identifying an inflection
point in the graph as the safe driving speed. Next, as shown at
block 310, the method 300 includes displaying an indication of the
safe driving speed to an operator of the vehicle. In exemplary
embodiments, the safe driving speed can be displayed on a heads-up
display of a vehicle, a driver information panel of the vehicle, on
a display of a smartphone or the like.
[0052] In exemplary embodiments, the method can also include
generating an alert based on a determination that a current speed
of the vehicle is greater than the safe driving speed. For example,
the alert can be an audio alert, such as a beeping sound, that is
used to indicate that the current speed of the vehicle is greater
than the safe driving speed. The volume and/or frequency of this
alert may increase as the difference between the current speed and
the safe driving speed increases.
[0053] In exemplary embodiments, the method can also include
limiting a current speed of the vehicle to the safe driving speed.
For example, the vehicle may receive the safe driving speed and may
electronically limit the operating speed of the vehicle to the safe
driving speed. In addition, the vehicle may be configured to
automatically adjust a speed of a cruise control of the vehicle to
be equal to the safe driving speed.
[0054] Referring now to FIG. 6, a flow diagram of a method 400
determining a safe driving speed for a vehicle in accordance with
an exemplary embodiment. As shown at block 402, the method 400
includes installing a safe speed determination system in their
vehicle or on their smartphone. Next, as shown at block 404, the
method 400 includes the safe speed determination system obtaining a
current location and speed of the vehicle as well as the time of
day, weather information, traffic information and other relevant
information. The method 500 includes obtaining accident data that
was reported under similar conditions from one or more databases,
as shown at block 406. Next, as shown at block 408, the method 400
includes diving the road into zones based on a clustering of
accidents reflected in the obtained data. A graph is constructed
using the accident data for each zone of the road, as shown at
block 410. In one embodiment, the graph can be a graph as shown in
FIGS. 7 and 8, which illustrate a normalized number of accidents
and the speed at which the accident occurred. The normalized number
of accidents for each speed can be calculated by dividing the
number of accidents at X mph by the number of cars driving at X
mph. Next, as shown at block 412, the method 400 includes
identifying an inflection point on the graph to determine the safe
driving speed. As shown at block 414, the method 400 includes
displaying the safe driving speed to the driver of the vehicle.
[0055] In another embodiment, a percentage cutoff rather than an
inflection point may be used to identifying the safe driving speed.
For example, the safe driving speed may be determined to be the
speed at which more than thirty-three percent of the cars traveling
at a given speed were involved in an accident, as shown FIG. 8.
[0056] In one example, a model is constructed that includes a
normalized number of drivers in a given speed zone that had a
traffic accident when going x miles per hour, where x is the
horizontal axis of the curve. The normalized number of accidents
for each speed can be calculated by dividing the number of
accidents at X mph by the number of cars driving at X mph. From the
model, a safe driving speed range can be calculated for the driver
given weather condition, the day of the week, and time of the day.
The model can be constructed on demand and will change when the
driver approaches a new speed zone in which the speed zone is
higher or lower than the current speed zone. From the given range,
the upper bound is identified as the safe driving speed on the
current road with a reduced chance of having a traffic accident for
the given weather conditions, the day of the week, and time of
day.
[0057] In one example, a driver is approaching a road in which the
speed limit is 55 MPH at one in the afternoon on a Monday. The safe
driving speed system will identify the driver's location via GPS
and will identify that current weather is sunny for that location.
Pulling traffic accident data for that zone, a model is
constructed, 2/100 people have had an accident going less than 55
MPH, 4/100 people have had an accident going between 56-60 MPH,
8/100 people have had an accident going between 61-64 MPH, 12/100
people have had an accident going between 65-68 MPH, and 42/100
people have had an accident going greater than 69 MPH in similar
weather conditions, day of the week, and time of day. The safe
driving speed system will identify the least risky speed range as
less than 61 MPH and will return 61 at the `safe` speed for the
current speed zone.
[0058] The present invention may be a system, a method, and/or a
computer program product. The computer program product may include
a computer readable storage medium (or media) having computer
readable program instructions thereon for causing a processor to
carry out aspects of the present invention.
[0059] The computer readable storage medium can be a tangible
device that can retain and store instructions for use by an
instruction execution device. The computer readable storage medium
may be, for example, but is not limited to, an electronic storage
device, a magnetic storage device, an optical storage device, an
electromagnetic storage device, a semiconductor storage device, or
any suitable combination of the foregoing. A non-exhaustive list of
more specific examples of the computer readable storage medium
includes the following: a portable computer diskette, a hard disk,
a random access memory (RAM), a read-only memory (ROM), an erasable
programmable read-only memory (EPROM or Flash memory), a static
random access memory (SRAM), a portable compact disc read-only
memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a
floppy disk, a mechanically encoded device such as punch-cards or
raised structures in a groove having instructions recorded thereon,
and any suitable combination of the foregoing. A computer readable
storage medium, as used herein, is not to be construed as being
transitory signals per se, such as radio waves or other freely
propagating electromagnetic waves, electromagnetic waves
propagating through a waveguide or other transmission media (e.g.,
light pulses passing through a fiber-optic cable), or electrical
signals transmitted through a wire.
[0060] Computer readable program instructions described herein can
be downloaded to respective computing/processing devices from a
computer readable storage medium or to an external computer or
external storage device via a network, for example, the Internet, a
local area network, a wide area network and/or a wireless network.
The network may comprise copper transmission cables, optical
transmission fibers, wireless transmission, routers, firewalls,
switches, gateway computers and/or edge servers. A network adapter
card or network interface in each computing/processing device
receives computer readable program instructions from the network
and forwards the computer readable program instructions for storage
in a computer readable storage medium within the respective
computing/processing device.
[0061] Computer readable program instructions for carrying out
operations of the present invention may be assembler instructions,
instruction-set-architecture (ISA) instructions, machine
instructions, machine dependent instructions, microcode, firmware
instructions, state-setting data, or either source code or object
code written in any combination of one or more programming
languages, including an object oriented programming language such
as Smalltalk, C++ or the like, and conventional procedural
programming languages, such as the "C" programming language or
similar programming languages. The computer readable program
instructions may execute entirely on the user's computer, partly on
the user's computer, as a stand-alone software package, partly on
the user's computer and partly on a remote computer or entirely on
the remote computer or server. In the latter scenario, the remote
computer may be connected to the user's computer through any type
of network, including a local area network (LAN) or a wide area
network (WAN), or the connection may be made to an external
computer (for example, through the Internet using an Internet
Service Provider). In some embodiments, electronic circuitry
including, for example, programmable logic circuitry,
field-programmable gate arrays (FPGA), or programmable logic arrays
(PLA) may execute the computer readable program instructions by
utilizing state information of the computer readable program
instructions to personalize the electronic circuitry, in order to
perform aspects of the present invention.
[0062] Aspects of the present invention are described herein with
reference to flowchart illustrations and/or block diagrams of
methods, apparatus (systems), and computer program products
according to embodiments of the invention. It will be understood
that each block of the flowchart illustrations and/or block
diagrams, and combinations of blocks in the flowchart illustrations
and/or block diagrams, can be implemented by computer readable
program instructions.
[0063] These computer readable program instructions may be provided
to a processor of a general purpose computer, special purpose
computer, or other programmable data processing apparatus to
produce a machine, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or blocks.
These computer readable program instructions may also be stored in
a computer readable storage medium that can direct a computer, a
programmable data processing apparatus, and/or other devices to
function in a particular manner, such that the computer readable
storage medium having instructions stored therein comprises an
article of manufacture including instructions which implement
aspects of the function/act specified in the flowchart and/or block
diagram block or blocks.
[0064] The computer readable program instructions may also be
loaded onto a computer, other programmable data processing
apparatus, or other device to cause a series of operational steps
to be performed on the computer, other programmable apparatus or
other device to produce a computer implemented process, such that
the instructions which execute on the computer, other programmable
apparatus, or other device implement the functions/acts specified
in the flowchart and/or block diagram block or blocks.
[0065] The flowchart and block diagrams in the Figures illustrate
the architecture, functionality, and operation of possible
implementations of systems, methods, and computer program products
according to various embodiments of the present invention. In this
regard, each block in the flowchart or block diagrams may represent
a module, segment, or portion of instructions, which comprises one
or more executable instructions for implementing the specified
logical function(s). In some alternative implementations, the
functions noted in the block may occur out of the order noted in
the figures. For example, two blocks shown in succession may, in
fact, be executed substantially concurrently, or the blocks may
sometimes be executed in the reverse order, depending upon the
functionality involved. It will also be noted that each block of
the block diagrams and/or flowchart illustration, and combinations
of blocks in the block diagrams and/or flowchart illustration, can
be implemented by special purpose hardware-based systems that
perform the specified functions or acts or carry out combinations
of special purpose hardware and computer instructions.
* * * * *